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Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/ai-102
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Microsoft AI-102日本語 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Plan and manage an Azure AI solution | 20-25% | - Choose services for generative AI, computer vision, NLP, speech, information extraction, knowledge mining - Monitor, optimize, and secure AI solutions - Plan solutions aligned with responsible AI principles - Select suitable AI models - Create and configure Azure AI resources - Select appropriate Microsoft Foundry Services |
| Implement knowledge mining and information extraction solutions | 15-20% | - Extract entities, relationships, and key phrases - Ingest and process structured/unstructured data - Build knowledge bases and search indexes - Implement intelligent search and retrieval |
| Implement computer vision solutions | 10-15% | - Analyze images and detect objects/features - Extract text and handwriting from images - Build and deploy custom vision models - Integrate vision capabilities into applications - Process and index video content |
| Implement an agentic solution | 5-10% | - Build agents with Microsoft Foundry Agent Service - Develop multi-agent workflows and orchestration - Test, deploy, and optimize agents - Understand agent use cases and types |
| Implement natural language processing solutions | 15-20% | - Build conversational AI and chatbots - Perform text analysis, sentiment detection, and language detection - Implement translation and summarization - Customize and deploy NLP models |
| Implement generative AI solutions | 15-20% | - Implement model monitoring and feedback - Deploy and manage generative models - Apply prompt engineering and fine-tuning - Integrate Azure OpenAI and other generative models - Orchestrate multiple models and containers |






